意图识别：支持自定义。

Author: wangliang181230

apps/application/flow/step_node/ai_chat_step_node/impl/base_chat_node.py

@@ -167,13 +167,14 @@ def execute(self, model_id, system, prompt, dialogue_number, history_chat_record
 
         if model_params_setting is None:
             model_params_setting = get_default_model_params_setting(model_id)
+
         if model_setting is None:
             model_setting = {'reasoning_content_enable': False, 'reasoning_content_end': '</think>',
                              'reasoning_content_start': '<think>'}
         self.context['model_setting'] = model_setting
         workspace_id = self.workflow_manage.get_body().get('workspace_id')
         chat_model = get_model_instance_by_model_workspace_id(model_id, workspace_id,
-                                                              **model_params_setting)
+                                                              **(model_params_setting or {}))
         history_message = self.get_history_message(history_chat_record, dialogue_number, dialogue_type,
                                                    self.runtime_node_id)
         self.context['history_message'] = [{'content': message.content, 'role': message.type} for message in

apps/application/flow/step_node/image_generate_step_node/impl/base_image_generate_node.py

@@ -28,7 +28,7 @@ def execute(self, model_id, prompt, negative_prompt, dialogue_number, dialogue_t
                 **kwargs) -> NodeResult:
         workspace_id = self.workflow_manage.get_body().get('workspace_id')
         tti_model = get_model_instance_by_model_workspace_id(model_id, workspace_id,
-                                                             **model_params_setting)
+                                                             **(model_params_setting or {}))
         history_message = self.get_history_message(history_chat_record, dialogue_number)
         self.context['history_message'] = history_message
         question = self.generate_prompt_question(prompt)

apps/application/flow/step_node/image_to_video_step_node/impl/base_image_to_video_node.py

@@ -32,7 +32,7 @@ def execute(self, model_id, prompt, negative_prompt, dialogue_number, dialogue_t
                 **kwargs) -> NodeResult:
         workspace_id = self.workflow_manage.get_body().get('workspace_id')
         ttv_model = get_model_instance_by_model_workspace_id(model_id, workspace_id,
-                                                             **model_params_setting)
+                                                             **(model_params_setting or {}))
         history_message = self.get_history_message(history_chat_record, dialogue_number)
         self.context['history_message'] = history_message
         question = self.generate_prompt_question(prompt)

apps/application/flow/step_node/image_understand_step_node/i_image_understand_node.py

@@ -43,7 +43,7 @@ def _run(self):
         if [WorkflowMode.KNOWLEDGE, WorkflowMode.KNOWLEDGE_LOOP].__contains__(
                 self.workflow_manage.flow.workflow_mode):
             return self.execute(image=res, **self.node_params_serializer.data, **self.flow_params_serializer.data,
-                                **{'history_chat_record': [], 'stream': True,  'chat_record_id': None})
+                                **{'history_chat_record': [], 'stream': True, 'chat_record_id': None})
         else:
             return self.execute(image=res, **self.node_params_serializer.data, **self.flow_params_serializer.data)
 

apps/application/flow/step_node/intent_node/impl/base_intent_node.py

@@ -12,7 +12,7 @@
 from application.flow.step_node.intent_node.i_intent_node import IIntentNode
 from models_provider.models import Model
 from models_provider.tools import get_model_instance_by_model_workspace_id, get_model_credential
-from .prompt_template import PROMPT_TEMPLATE
+from .prompt_template import DEFAULT_PROMPT_TEMPLATE
 
 
 def get_default_model_params_setting(model_id):
@@ -52,7 +52,7 @@ def save_context(self, details, workflow_manage):
         self.context['branch_id'] = details.get('branch_id')
         self.context['category'] = details.get('category')
 
-    def execute(self, model_id, dialogue_number, history_chat_record, user_input, branch, output_reason,
+    def execute(self, model_id, prompt_template, dialogue_number, history_chat_record, user_input, branch, output_reason,
                 model_params_setting=None, **kwargs) -> NodeResult:
 
         # 设置默认模型参数
@@ -62,7 +62,7 @@ def execute(self, model_id, dialogue_number, history_chat_record, user_input, br
         # 获取模型实例
         workspace_id = self.workflow_manage.get_body().get('workspace_id')
         chat_model = get_model_instance_by_model_workspace_id(
-            model_id, workspace_id, **model_params_setting
+            model_id, workspace_id, **(model_params_setting or {})
         )
 
         # 获取历史对话
@@ -73,7 +73,8 @@ def execute(self, model_id, dialogue_number, history_chat_record, user_input, br
         self.context['user_input'] = user_input
 
         # 构建分类提示词
-        prompt = self.build_classification_prompt(user_input, branch, output_reason)
+        prompt_template = self.workflow_manage.generate_prompt(prompt_template) if prompt_template else None
+        prompt = self.build_classification_prompt(prompt_template, user_input, branch, output_reason)
         self.context['system'] = prompt
 
         # 生成消息列表
@@ -95,7 +96,7 @@ def execute(self, model_id, dialogue_number, history_chat_record, user_input, br
                 'history_message': history_message,
                 'user_input': user_input,
                 'branch_id': matched_branch['id'],
-                'reason': self.parse_result_reason(r.content) if output_reason is True else '',
+                'reason': self.parse_result_reason(r.content) if output_reason is not False else '',
                 'category': matched_branch.get('content', matched_branch['id'])
             }, {}, _write_context=write_context)
 
@@ -125,7 +126,7 @@ def get_history_message(history_chat_record, dialogue_number):
                 message.content = re.sub('<form_rander>[\d\D]*?<\/form_rander>', '', message.content)
         return history_message
 
-    def build_classification_prompt(self, user_input: str, branch: List[Dict], output_reason: bool) -> str:
+    def build_classification_prompt(self, prompt_template: str, user_input: str, branch: List[Dict], output_reason: bool) -> str:
         """构建分类提示词"""
 
         classification_list = []
@@ -148,10 +149,10 @@ def build_classification_prompt(self, user_input: str, branch: List[Dict], outpu
                 classification_id += 1
 
         # 构建输出JSON结构
-        output_reason = ',\n"reason": ""' if output_reason is True else ''
-        output_json = f'{{\n"classificationId": 0{output_reason}\n}}'
+        reason_field = ',\n"reason": ""' if output_reason is not False else ''
+        output_json = f'{{\n"classificationId": 0{reason_field}\n}}'
 
-        return PROMPT_TEMPLATE.format(
+        return (prompt_template or DEFAULT_PROMPT_TEMPLATE).format(
             classification_list=json.dumps(classification_list, ensure_ascii=False),
             user_input=user_input,
             output_json=output_json
@@ -179,8 +180,17 @@ def get_branch_by_id(category_id: int):
             return None
 
         try:
-            result_json = json.loads(result)
-            classification_id = result_json.get('classificationId')
+            classification_id = None
+
+            # 如果长度小于5，先尝试解析为数字（增加自由度，在自定义提示词模板时，可提示大模型只输出意图分类的ID值）
+            if len(result) < 5:
+                classification_id = self.to_int(result)
+
+            # 尝试解析为 JSON
+            if classification_id is None:
+                result_json = json.loads(result)
+                classification_id = result_json.get('classificationId')
+
             # 如果是 0 ，返回其他分支
             matched_branch = get_branch_by_id(classification_id)
             if matched_branch:
@@ -220,6 +230,12 @@ def parse_result_reason(self, result: str):
 
             return ''
 
+    def to_int(self, str):
+        try:
+            return int(str)
+        except ValueError:
+            return None
+
     def find_other_branch(self, branch: List[Dict]) -> Dict[str, Any] | None:
         """查找其他分支"""
         for b in branch:

apps/application/flow/step_node/intent_node/impl/prompt_template.py

@@ -1,6 +1,6 @@
 
 
-PROMPT_TEMPLATE = """# Role
+DEFAULT_PROMPT_TEMPLATE = """# Role
 You are an intention classification expert, good at being able to judge which classification the user's input belongs to.
 
 ## Skills

apps/application/flow/step_node/parameter_extraction_node/impl/base_parameter_extraction_node.py

@@ -98,7 +98,8 @@ def execute(self, input_variable, variable_list, model_params_setting, model_id,
             model_params_setting = get_default_model_params_setting(model_id)
         workspace_id = self.workflow_manage.get_body().get('workspace_id')
         chat_model = get_model_instance_by_model_workspace_id(model_id, workspace_id,
-                                                              **model_params_setting)
+                                                              **(model_params_setting or {}))
+
         content = generate_content(input_variable, variable_list)
         response = chat_model.invoke([HumanMessage(content=content)])
         result = json_loads(response.content, variable_list)

apps/application/flow/step_node/question_node/impl/base_question_node.py

@@ -90,7 +90,7 @@ def execute(self, model_id, system, prompt, dialogue_number, history_chat_record
             model_params_setting = get_default_model_params_setting(model_id)
         workspace_id = self.workflow_manage.get_body().get('workspace_id')
         chat_model = get_model_instance_by_model_workspace_id(model_id, workspace_id,
-                                                              **model_params_setting)
+                                                              **(model_params_setting or {}))
         history_message = self.get_history_message(history_chat_record, dialogue_number)
         self.context['history_message'] = history_message
         question = self.generate_prompt_question(prompt)

apps/application/flow/step_node/speech_to_text_step_node/impl/base_speech_to_text_node.py

@@ -23,7 +23,7 @@ def save_context(self, details, workflow_manage):
 
     def execute(self, stt_model_id, audio, model_params_setting=None, **kwargs) -> NodeResult:
         workspace_id = self.workflow_manage.get_body().get('workspace_id')
-        stt_model = get_model_instance_by_model_workspace_id(stt_model_id, workspace_id, **model_params_setting)
+        stt_model = get_model_instance_by_model_workspace_id(stt_model_id, workspace_id, **(model_params_setting or {}))
         audio_list = audio
         self.context['audio_list'] = audio
 

apps/application/flow/step_node/text_to_speech_step_node/impl/base_text_to_speech_node.py

@@ -60,7 +60,7 @@ def execute(self, tts_model_id,
             self.context['content'] = chunk
             workspace_id = self.workflow_manage.get_body().get('workspace_id')
             model = get_model_instance_by_model_workspace_id(
-                tts_model_id, workspace_id, **model_params_setting)
+                tts_model_id, workspace_id, **(model_params_setting or {}))
 
             audio_byte = model.text_to_speech(chunk)